Graph and download economic data for Resident Population in the Midwest Census Region (CMWRPOP) from 1900 to 2024 about Midwest Census Region, residents, population, and USA.

About this dataset

Context

The dataset tabulates the Midwest population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for Midwest. The dataset can be utilized to understand the population distribution of Midwest by age. For example, using this dataset, we can identify the largest age group in Midwest.

Key observations

The largest age group in Midwest, WY was for the group of age 50 to 54 years years with a population of 42 (19.27%), according to the ACS 2019-2023 5-Year Estimates. At the same time, the smallest age group in Midwest, WY was the Under 5 years years with a population of 0 (0%). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group in consideration
• Population: The population for the specific age group in the Midwest is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Midwest total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Midwest Population by Age. You can refer the same here

Resident Population in the Midwest Census Region was 69596.58400 Thous. of Persons in January of 2024, according to the United States Federal Reserve. Historically, Resident Population in the Midwest Census Region reached a record high of 69596.58400 in January of 2024 and a record low of 26359.00000 in January of 1900. Trading Economics provides the current actual value, an historical data chart and related indicators for Resident Population in the Midwest Census Region - last updated from the United States Federal Reserve on September of 2025.

Graph and download economic data for Unemployed Persons in Midwest Census Region (LAURD920000000000004) from Jan 1976 to Jul 2025 about Midwest Census Region, household survey, persons, unemployment, and USA.

Graph and download economic data for Employed Persons in Midwest Census Region (LASRD920000000000005) from Jan 1976 to Jul 2025 about Midwest Census Region, persons, household survey, employment, and USA.

About this dataset

Context

The dataset tabulates the Midwest population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Midwest across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2022, the population of Midwest was 284, a 0.35% decrease year-by-year from 2021. Previously, in 2021, Midwest population was 285, a decline of 0.70% compared to a population of 287 in 2020. Over the last 20 plus years, between 2000 and 2022, population of Midwest decreased by 101. In this period, the peak population was 420 in the year 2013. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2022

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2022)
• Population: The population for the specific year for the Midwest is shown in this column.
• Year on Year Change: This column displays the change in Midwest population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Midwest Population by Year. You can refer the same here

This statistic shows the change in the regional distribution of the U.S. population each decade from 1790 to 2021. In 2021, 17.2 percent of the population in the United States lived in the Northeast.

Graph and download economic data for Civilian Labor Force in Midwest Census Region (LAURD920000000000006A) from 1976 to 2024 about Midwest Census Region, civilian, labor force, labor, household survey, and USA.

This dataset includes microsatellite genotypes for 8,454 brook trout from 188 wild Midwestern populations and 26 hatchery strains of both Midwest and eastern (Atlantic seaboard) origin. Each individual was genotyped at either 5 or 7 loci.

About this dataset

Context

The dataset tabulates the Midwest City population by age cohorts (Children: Under 18 years; Working population: 18-64 years; Senior population: 65 years or more). It lists the population in each age cohort group along with its percentage relative to the total population of Midwest City. The dataset can be utilized to understand the population distribution across children, working population and senior population for dependency ratio, housing requirements, ageing, migration patterns etc.

Key observations

The largest age group was 18 to 64 years with a poulation of 33,265 (57.19% of the total population). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Age cohorts:

• Under 18 years
• 18 to 64 years
• 65 years and over

Variables / Data Columns

• Age Group: This column displays the age cohort for the Midwest City population analysis. Total expected values are 3 groups ( Children, Working Population and Senior Population).
• Population: The population for the age cohort in Midwest City is shown in the following column.
• Percent of Total Population: The population as a percent of total population of the Midwest City is shown in the following column.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Midwest City Population by Age. You can refer the same here

About this dataset

Context

The dataset tabulates the data for the Midwest, WY population pyramid, which represents the Midwest population distribution across age and gender, using estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. It lists the male and female population for each age group, along with the total population for those age groups. Higher numbers at the bottom of the table suggest population growth, whereas higher numbers at the top indicate declining birth rates. Furthermore, the dataset can be utilized to understand the youth dependency ratio, old-age dependency ratio, total dependency ratio, and potential support ratio.

Key observations

• Youth dependency ratio, which is the number of children aged 0-14 per 100 persons aged 15-64, for Midwest, WY, is 5.7.
• Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for Midwest, WY, is 32.3.
• Total dependency ratio for Midwest, WY is 38.0.
• Potential support ratio, which is the number of youth (working age population) per elderly, for Midwest, WY is 3.1.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group for the Midwest population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Midwest for the selected age group is shown in the following column.
• Population (Female): The female population in the Midwest for the selected age group is shown in the following column.
• Total Population: The total population of the Midwest for the selected age group is shown in the following column.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Midwest Population by Age. You can refer the same here

12011 population data for individuals 18 years and older in Canada was obtained from Statistics Canada [36].22010 population data for individuals 18 years and older in the US was obtained from the US Census Bureau [38].3Regions were: Midwest (Illinois, Indiana, Iowa, Kansas, Michigan, Minnesota, Missouri, Nebraska, North Dakota, Ohio, South Dakota, Wisconsin); Northeast (Connecticut, Maine, Massachusetts, New Hampshire, New Jersey, New York, Pennsylvania, Rhode Island, Vermont); South (Alabama, Arkansas, Delaware, District of Columbia, Florida, Georgia, Kentucky, Louisiana, Maryland, Mississippi, North Carolina, Oklahoma, South Carolina, Tennessee, Texas, Virginia, West Virginia); West (Alaska, Arizona, California, Colorado, Hawaii, Idaho, Montana, Nevada, New Mexico, Oregon, Utah, Washington, Wyoming).42006 education data for individuals 20 years and over in Canada (most current and available data) [35].52010 education data for individuals 18 years and over in the US [37].*p

This dataset contains remotely sensed estimates of nitrogen dioxide (NO2, via TROPOMI accessed via Google Earth Engine) for HOLC neighborhoods in 11 US Midwestern cities, and corresponding coarse geographic and demographic data of those cities. NO2 data is reported daily for the entire calendar year of 2019, geographic and demographic variables are fixed for each city for the entire year. Each HOLC-graded neighborhood included in this dataset was filtered to be greater than 2 km2. The number of pixels used to calculate the area-weighted mean of NO2 is also reported, as is the area of the neighborhood. The dataset has also been filtered for observations that did not pass quality filters for L3 TROPOMI data. The cities included in the study are: Chicago IL, Milwaukee WI, Saint Paul MN, Minneapolis MN, Indianapolis IN, Cleveland OH, Wichita KS, Greater Kansas City KS and MO, Columbus OH, Detroit MI, and Omaha NE. HOLC neighborhood shapefiles were obtained from the Mapping Inequality project website, hosted by the University of Richmond, and resulting polygons used in analysis were created by dissolving shared boundaries in Google Earth Engine. City populations and population density were obtained from the US 2010 Census data. All data was collected and organized to assess if current day NO2 levels varied with HOLC grades in these major cities.

Data was used in the study: Hrycyna et al. (2022) Elementa 10(1):00027

Robert K. Nelson, LaDale Winling, Richard Marciano, Nathan Connolly, et al., “Mapping Inequality,” American Panorama, ed. https://dsl.richmond.edu/panorama/redlining/#loc=5/39.1/-94.58&text=downloads

Dataset for all analyses presented in Hrycyna et al. Columns described below:

HOLC_grade: A, B, C, D (neighborhood grade categories obtained from Mapping Inequality project, indicate historic HOLC designations of neighborhoods).

HOLCAreaKm2: continuous area value in km2 of the HOLC neighborhood polygon, which may be more than one HOLC designated polygon merged from the shapefiles downloaded from Mapping Inequality.

pixelcount: integer values of the number of TROPOMI NO2 pixels used to produce the area-weighted mean NO2 value.

NO2_mol_m2: area-weighted mean value of TROPOMI NO2 for that HOLC neighborhood polygon in mol m-2

system.index: designated date and time boundary of the observation collected via TROPOMI

date: date of observation

month: month of observation

City: city in the US Midwest

State: state for the city of focus

Population: urban population obtained from 2010 census

PopDensity: urban population density obtained from 2010 census, based on modern city boundaries (in people per square miles)

CityArea_mi2: Area of the city of interest, in square miles.

ln_NO2: natural log transformed NO2 values in mol m-2

NO2_DU: NO2 value converted from mol m-2 to DU (Dobsons Units, converted by multiplying 2241.15)

NO2_lnDU: natural log transformed NO2 values in DU

ObjectiveThere is currently inconclusive evidence regarding the relationship between recidivism and mental illness. This retrospective study aimed to use rigorous machine learning methods to understand the unique predictive utility of mental illness for recidivism in a general population (i.e.; not only those with mental illness) prison sample in the United States.MethodParticipants were adult men (n = 322) and women (n = 72) who were recruited from three prisons in the Midwest region of the United States. Three model comparisons using Bayesian correlated t-tests were conducted to understand the incremental predictive utility of mental illness, substance use, and crime and demographic variables for recidivism prediction. Three classification statistical algorithms were considered while evaluating model configurations for the t-tests: elastic net logistic regression (GLMnet), k-nearest neighbors (KNN), and random forests (RF).ResultsRates of substance use disorders were particularly high in our sample (86.29%). Mental illness variables and substance use variables did not add predictive utility for recidivism prediction over and above crime and demographic variables. Exploratory analyses comparing the crime and demographic, substance use, and mental illness feature sets to null models found that only the crime and demographics model had an increased likelihood of improving recidivism prediction accuracy.ConclusionsDespite not finding a direct relationship between mental illness and recidivism, treatment of mental illness in incarcerated populations is still essential due to the high rates of mental illnesses, the legal imperative, the possibility of decreasing institutional disciplinary burden, the opportunity to increase the effectiveness of rehabilitation programs in prison, and the potential to improve meaningful outcomes beyond recidivism following release.

In 2023, around 23.5 percent of those living in the Midwest of the United States had doctor-diagnosed arthritis in some form. This statistic displays the prevalence of doctor-diagnosed arthritis in the adult population in the United States from 2019 to 2023, by region.

The population name, site, year, densities, macroclimates, and microclimates are included. (XLSX)

IntroductionVariation in smoking cessation behaviors and motivators across the United States may contribute to health disparities. This study investigates regional differences over time in two key cessation motivators (quit interest and doctor's advice to quit) and two cessation behaviors (past-year quit attempts and recent successful cessation) across diverse demographic factors.MethodsData were analyzed from two releases of the Tobacco Use Supplement to the U.S. Census Bureau's Current Population Survey (TUS-CPS) for the years 2014–15 and 2018–19. The analysis included sex, age, race and ethnicity, education, marital status, employment status, and household income.ResultsFindings from 2018 to 2019 TUS-CPS revealed that quit interest was highest in the Northeast and lowest in the Midwest, while doctor's advice to quit was most prevalent in the Northeast and least in the West. Past-year quit attempts were most common in the Northeast and least in the South. Recent successful cessation (defined as quitting for 6 to 12 months) was highest in the Northeast and Midwest, with the South showing the lowest rates. Compared to the 2014–15 survey, 14 demographic groups (7 in the Midwest, 6 in the South, and 1 in the West) showed decreases in both quit interest and actions to quit. Notably, the Asian non-Hispanic group in the Northeast experienced a significant decrease in quit interest (–17.9%) but an increase in recent successful cessation (+369.2%).DiscussionOverall, the study indicates that while quit interest was highest in the West, the South exhibited the lowest rates of quit attempts and successful cessation. Significant differences were also noted between age groups. These findings highlight the need for further research into cessation behaviors at more granular levels to inform policies aimed at reducing smoking-related health disparities among populations facing the greatest challenges in cessation.

The adjusted-R2 value of each model is added to the last row of the table.

About this dataset

Context

The dataset tabulates the population of Midwest by gender, including both male and female populations. This dataset can be utilized to understand the population distribution of Midwest across both sexes and to determine which sex constitutes the majority.

Key observations

There is a majority of male population, with 56.42% of total population being male. Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis. No further analysis is done on the data reported from the Census Bureau.

Variables / Data Columns

• Gender: This column displays the Gender (Male / Female)
• Population: The population of the gender in the Midwest is shown in this column.
• % of Total Population: This column displays the percentage distribution of each gender as a proportion of Midwest total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Midwest Population by Race & Ethnicity. You can refer the same here

About this dataset

Context

The dataset tabulates the population of Midwest by race. It includes the population of Midwest across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of Midwest across relevant racial categories.

Key observations

The percent distribution of Midwest population by race (across all racial categories recognized by the U.S. Census Bureau): 94.50% are white, 3.21% are some other race and 2.29% are multiracial.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race: This column displays the racial categories (excluding ethnicity) for the Midwest
• Population: The population of the racial category (excluding ethnicity) in the Midwest is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Midwest total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Midwest Population by Race & Ethnicity. You can refer the same here